Data Storage, Integration and Analytical Tools
To provide the infrastructure and tools which will bring together genetic and other data from across the 6 participating countries.
A major part of this will be uniting the samples in an ethical and harmonized way, with standardized quality control.
Principal Investigator: Professor Eivind Hovig, Leader of the Center for Bioinformatics, Department of Informatics, University of Oslo
Existing data holds the clues
Which genes are linked to mental health ill-health and/or cardiovascular disease?
This is one of the key questions that CoMorMent hopes to address.
We believe that the answer to this question is already contained within existing datasets – if only we could bring them together and analyse them in a co-ordinated way. However, logistical difficulties are currently holding back research in this area.
Refine existing models
Existing models lack the subtlety required to predict who is at greatest risk of future ill-health.
To create better models, we need to bring lifestyle and behavioural factors into our analysis, and go beyond list of ‘symptoms’ and towards stratified medicine
[grouping patients based on their risk of disease or response to therapy. For example, ‘depression’ could be post-natal, situational, bipolar disorder etc. Each of these is likely to have a different underlying cause, mechanism and response to treatment]
Bring together international datasets
Our project aims to bring together high quality genetic, medical and lifestyle data from several different cohorts across our 6 partner countries.
Safe and secure infrastructure
We will make use of the Tryggve infrastructure (https://neic.no/tryggve/) which allows us to perform fast and safe analysis of our large data sets, in a way that adheres to the highest and latest privacy and ethical requirements.
Our approach ensures that the data and information remain within their country of origin, while still allowing analysis and quality control to be done across borders.
The Tryggve-supported framework includes several functions and algorithms which secure privacy and patient anonymity, allowing secure analysis of even sensitive samples and information.
Supporting the rest of the project
This Work Package will support the other scientific work packages (2,3,4, 5) by providing state-of-the-art analytical tools and receiving data /coordinating non-sharable data from each country.
A key element of this work will be the integration of the different data sources, who may have collected or recorded the same data in different ways (e.g. Male/Female/Other could be A, B, C or 1,2,3 depending on the dataset).
Work Package 1 will undertake a deeply systematic quality control (QC) process in order to synchronize the genetic and phenotype data from the different countries, to create one large-scale data-set for future analysis.
The CoMorMent project team includes several key members of the Nordic Tryggve initiative, which is designed to solve data sharing problems across borders.
CoMorMent includes partners from 6 different European countries, giving us access to data from over 1.8 million people – increasing our power for discoveries significantly.
Through WP1, we are linked to the ELIXIR Norway infrastructure program and will be able to leverage ELIXIR resources for the management of the WP.
Tekle KM, Gundersen S, Klepper K, et al. Norwegian e-Infrastructure for Life Sciences (NeLS). F1000Res. 2018;7:ELIXIR-968. Published 2018 Jun 29. doi:10.12688/f1000research.15119.1
Frei O, Holland D, Smeland OB, et al. Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation. Nat Commun. 2019;10(1):2417. Published 2019 Jun 3. doi:10.1038/s41467-019-10310-0